LINEST

known_ys: vector of values of dependent variable

known_xs: array of values of independent variables, defaults to a single vector {1,…,n}

affine: if true, the model contains a constant term, defaults to true

stats: if true, some additional statistics are provided, defaults to false

This function returns an array with the first row giving the regression coefficients for the independent variables x_m, x_(m-1),…,x_2, x_1 followed by the y-intercept if affine is true.

If stats is true, the second row contains the corresponding standard errors of the regression coefficients.In this case, the third row contains the R^2 value and the standard error for the predicted value. The fourth row contains the observed F value and its degrees of freedom. Finally, the fifth row contains the regression sum of squares and the residual sum of squares.

If affine is false, R^2 is the uncentered version of the coefficient of determination; that is the proportion of the sum of squares explained by the model.

If the length of known_ys does not match the corresponding length of known_xs, this function returns a #NUM! error.

LOGEST, TREND.